2 citations · 3 across the 4 of their papers we have counts for
4 papers
TransGUNet: Transformer Meets Graph-based Skip Connection for Medical Image Segmentation
Ju-Hyeon Nam, Nur Suriza Syazwany, Sang-Chul Lee
Skip connection engineering is primarily employed to address the semantic gap between the encoder and decoder, while also integrating global dependencies to understand the relation…
Modality-agnostic Domain Generalizable Medical Image Segmentation by Multi-Frequency in Multi-Scale Attention
Ju-Hyeon Nam, Nur Suriza Syazwany, Su Jung Kim +1
Generalizability in deep neural networks plays a pivotal role in medical image segmentation. However, deep learning-based medical image analyses tend to overlook the importance of…
M3FPolypSegNet: Segmentation Network with Multi-frequency Feature Fusion for Polyp Localization in Colonoscopy Images
Ju-Hyeon Nam, Seo-Hyeong Park, Nur Suriza Syazwany +3
Polyp segmentation is crucial for preventing colorectal cancer a common type of cancer. Deep learning has been used to segment polyps automatically, which reduces the risk of misdi…
Local Feature Extraction from Salient Regions by Feature Map Transformation
Yerim Jung, Nur Suriza Syazwany Binti Ahmad Nizam, Sang-Chul Lee
Local feature matching is essential for many applications, such as localization and 3D reconstruction. However, it is challenging to match feature points accurately in various came…